Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry , Rheinische Friedrich-Wilhelms-Universität , Endenicher Allee 19c , D-53115 Bonn , Germany.
J Med Chem. 2018 Dec 13;61(23):10895-10900. doi: 10.1021/acs.jmedchem.8b01626. Epub 2018 Nov 30.
In medicinal chemistry, lead optimization is a critically important task and a highly empirical process, largely driven by chemical knowledge and intuition. Only very few approaches are available to guide and evaluate optimization efforts. It is often very difficult to understand when a compound series is exhausted and the generation of additional analogs unlikely to yield further progress toward potent and efficacious candidates. Rationalizing lead optimization remains an essentially unsolved problem. Herein, we introduce a new computational method to aid in evaluating whether sufficient numbers of analogs have been made and further progress is unlikely. The approach integrates the assessment of chemical saturation and structure-activity relationship progression of compound series. Easy-to-calculate scores characterize evolving analog series and identify candidates with high or low priority for further chemical exploration.
在药物化学中，先导化合物优化是一项至关重要的任务，也是一个高度经验性的过程，主要依赖于化学知识和直觉。只有极少数方法可用于指导和评估优化工作。通常很难确定化合物系列是否已经用尽，并且进一步生成类似物不太可能取得进一步的进展，从而得到有效候选物。合理化先导化合物优化仍然是一个未解决的基本问题。在此，我们引入了一种新的计算方法，以帮助评估是否已经生成了足够数量的类似物，并且进一步的进展不太可能。该方法整合了对化合物系列的化学饱和和构效关系进展的评估。易于计算的分数可表征不断发展的类似物系列，并确定具有高优先级或低优先级的候选物，以进行进一步的化学探索。
